JMLR
2010
13 years 6 months ago
2010
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
FSS
2008
13 years 10 months ago
2008
We propose new types of linguistic summaries of time-series data that extend those proposed in our previous papers. The proposed summaries of time series refer to the summaries of...
NIPS
2008
14 years 29 days ago
2008
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
SIGMOD
2010
ACM
14 years 4 months ago
2010
ACM
We propose PASTE, the first differentially private aggregation algorithms for distributed time-series data that offer good practical utility without any trusted server. PASTE add...
ICDM
2006
IEEE
14 years 5 months ago
2006
IEEE
In this paper, we propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of ...
ICPR
2008
IEEE
14 years 6 months ago
2008
IEEE
Novelty detection is concerned with identifying abnormal system behaviours and abrupt changes from one regime to another. This paper proposes an on-line (causal) novelty detection...